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Synopsys

EDA software for chip design

Program Management Principal - Technical

Program ManagementConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • A bachelor's or master's degree in Computer Science, Engineering, Data Science, Information Systems, or a related technical discipline.
  • At least 12 years of experience leading complex, enterprise-scale technical programs within software, semiconductor, cloud, artificial intelligence, or high-tech environments.
  • Experience building or operating artificial intelligence governance, responsible artificial intelligence, technology risk, compliance, cybersecurity, or enterprise transformation programs.
  • Strong understanding of generative artificial intelligence, large language models, agentic artificial intelligence, artificial intelligence platforms, and artificial intelligence adoption challenges within large organizations.
  • Experience coordinating cross-functional reviews involving Legal, Privacy, Cybersecurity, Compliance, Product, Engineering, and business stakeholders.
  • Experience with portfolio management and workflow tools such as Jira, SharePoint, and Confluence.
  • Ability to translate complex artificial intelligence governance and risk topics into clear, actionable guidance for executives, engineers, and business leaders while retaining technical nuance.
  • Ability to influence across organizations and executive levels without direct authority by building trust and alignment through credibility, clarity, and follow-through.
  • Ability to operate amid ambiguity and build governance structures and processes as technology, policy, and business objectives evolve.
  • Ability to connect artificial intelligence technology capabilities, governance requirements, risk management, and business value so that governance enables progress.
  • Ability to manage multiple high-stakes initiatives simultaneously, keep stakeholders aligned, maintain timelines, and advance deliverables.
  • A point of view on effective artificial intelligence governance and willingness to challenge vague policies, slow processes, or incomplete risk assessments.

Responsibilities

  • Lead and scale the enterprise artificial intelligence governance operating model across generative artificial intelligence, large language models, agentic artificial intelligence, third-party artificial intelligence solutions, and internal artificial intelligence applications; establish processes for intake, evaluation, approval, monitoring, risk management, and lifecycle oversight.
  • Partner with Legal, Cybersecurity, Privacy, Compliance, Procurement, Engineering, Product, Information Technology, and business stakeholders to evaluate artificial intelligence technologies and use cases, aligning risk, regulatory compliance, intellectual property protection, privacy, and security requirements.
  • Operationalize governance frameworks, including the NIST Artificial Intelligence Risk Management Framework, ISO/IEC 42001, and responsible artificial intelligence principles, translating them into practical workflows that balance innovation velocity with enterprise risk.
  • Define governance patterns for agentic artificial intelligence systems, including access controls, monitoring, auditability, and lifecycle management, in partnership with research and development teams to ensure safe and responsible deployment.
  • Drive artificial intelligence academy initiatives with People and business leaders to build artificial intelligence literacy, responsible artificial intelligence awareness, and role-specific artificial intelligence skills across the organization; develop adoption playbooks and enablement programs.
  • Develop governance metrics, executive dashboards, and reporting mechanisms to drive transparency, accountability, and continuous improvement across artificial intelligence adoption and risk management.
  • Support strategic artificial intelligence ecosystem partnerships, platform evaluations, and technology provider assessments, contributing to enterprise artificial intelligence strategy, adoption roadmaps, and executive communications.
  • Provide executive leadership visibility into artificial intelligence adoption, risk posture, and business impact through metrics, dashboards, and reporting that inform strategic decision-making.
  • Build governance mechanisms that adapt to evolving artificial intelligence technologies, regulatory requirements, and business needs.

Desired Qualifications

  • Familiarity with governance and risk frameworks such as the NIST Artificial Intelligence Risk Management Framework, ISO/IEC 42001, and emerging artificial intelligence regulatory requirements.
  • Experience driving enterprise adoption, change management, workforce enablement, or artificial intelligence upskilling initiatives.

About the Company

Synopsys

EDA software for chip design

Synopsys provides software tools and services for electronic design automation (EDA), helping engineers design, simulate, verify, and optimize semiconductor chips and systems. Its products cover the full design flow, including RTL-to-gating synthesis, place-and-route, timing analysis, verification, and silicon validation, as well as software integrity solutions and hardware-assisted verification. Engineers use these tools to model, simulate, and validate complex chip designs before manufacturing, reducing bugs and improving performance. Compared with many competitors, Synopsys differentiates itself through its broad, end-to-end design toolchain, large ecosystem of IP and integration with simulation and modeling capabilities gained from its 2025 merger with ANSYS, and its global scale and support. The company aims to help designers push the boundaries of chip and system performance, accelerate time-to-market, and enable silicon-to-systems design across a wide range of industries.

Company size
10,001+
Company stage
IPO
Headquarters
Sunnyvale, CA
Founded
1986

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